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External quality assurance project report for the National Atmospheric Deposition Program’s National Trends Network and Mercury Deposition Network, 2017–18

The U.S. Geological Survey (USGS) Precipitation Chemistry Quality Assurance project (PCQA) operated five distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program’s (NADP) National Trends Network and Mercury Deposition Network during 2017–18. The National Trends Network programs included (1) a field audit program to evaluate sample contamination and stability, (2) an interlaboratory comparison program to evaluate analytical laboratory performance, and (3) a colocated sampler program to evaluate variability attributed to automated precipitation samplers. The Mercury Deposition Network programs include the (4) system blank program and (5) an interlaboratory comparison program. The results indicate consistently low levels of sample contamination, generally strong analytical laboratory performance, and low overall variability in concentration data imparted by field equipment. The NADP operations moved from its 40-year home at the Illinois State Water Survey to the Wisconsin State Laboratory of Hygiene in June 2018. The PCQA programs were modified and (or) temporarily curtailed during the transition in 2018. Bias and variability of sample analysis results were evaluated for the two Central Analytical Laboratories, and ongoing monitoring will be helpful to differentiate true environmental signals from the effects of changing laboratory conditions and performance. Results of quality assurance sample analyses are provided to document that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends for chemical constituents in wet deposition.

Scientific Investigations Report↗

Environmental DNA dynamics of three species of unionid freshwater mussels

North American freshwater mussels are of special conservation concern due to their high endemism and the multiple anthropogenic stressors affecting them. Of the over 300 species in North America, nearly one third of these species are federally listed as threatened or endangered. Environmental DNA (eDNA) analysis has been successful in detecting freshwater mussels and could aid in monitoring their populations. Production and degradation rates of eDNA for the species of interest are needed to inform interpretation of eDNA detections, allow possible modeling of relative abundance and population location, and aid in mussel conservation through population identification. Here, we designed and tested qPCR assays for three freshwater mussel species, mucket ( Ortmanniana ligamentina ), fatmucket ( Lampsilis siliquoidea ), and the federally endangered spectaclecase ( Cumberlandia monodonta ). We performed laboratory experiments under controlled conditions to measure eDNA shedding and degradation rates for each species. Different biomasses, temperatures, and food regimens were tested independently to determine if these factors influence the amount of DNA produced by the mussels. Degradation rates of eDNA were measured from experimental tank water after mussels were removed. Overall, we observed low eDNA shedding rates for freshwater mussels compared to previous studies of fish eDNA shedding rates. Furthermore, temperature and feeding showed limited or no significant effects in the species studied. Environmental DNA degradation rates were consistent with those reported in the literature for other taxa. Collectively, our results will be useful for designing eDNA monitoring studies, modeling eDNA dispersal, and interpreting eDNA results to help inform freshwater mussel conservation efforts.

Environmental DNA↗

Water resources of Lincoln County, Wyoming

Streamflow and ground-water quantity and quality data were collected and analyzed, 1993 through 1995, and historical data were compiled to summarize the water resources of Lincoln County.Deposits of Quaternary age, in the valleys of the Bear River and Salt River, had the most well development of any geologic unit in the county.The most productive alluvial aquifers were located in the Bear River Valley and Star Valley with pumping wells discharging up to 2,000 gallons perminute. The ground-water connection between the Overthrust Belt and the Green River Basin is restricted as a result of the folding and faulting that occurred during middle Mesozoic and early Cenozoic time. Total water use in Lincoln County during 1993 was estimated to be 405,000 million gallons. Surface water was the source for 98 percent of the water used in the county. Hydroelectric power generation and irrigation used the largest amounts of water. Dissolved-solids concentrations varied greatly for water samples collected from 35 geologic units inventoried. Dissolved-solids concentrations in all water samples from the LaneyMember of the Green River Formation were greater than the Secondary Maximum Contaminant Level of 500 milligrams per liter established by the U.S. Environmental Protection Agency. Statistical analysis of data collected from wells in the Star Valley monitoring study indicated there was no significant difference between data collected during different seasons, and no correlation between the nitrate concentrations and depth to ground water.

Wyoming↗

Environmental immunoassays: Alternative techniques for soil and water analysis

Analysis of soil and water samples for environmental studies and compliance testing can be formidable, time consuming, and costly. As a consequence, immunochemical techniques have become popular for environmental analysis because they are reliable, rapid, and cost effective. During the past 5 years, the use of immunoassays for environmental monitoring has increased substantially, and their use as an integral analytical tool in many environmental laboratories is now commonplace. This chapter will present the basic concept of immunoassays, recent advances in the development of immunochemical methods, and examples of successful applications of immunoassays in environmental analysis.

ACS Symposium Series↗

An analytical framework for estimating aquatic species density from environmental DNA

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

Ecology and Evolution↗

Land-cover change in the central irregular plains, 1973-2000

Spearheaded by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in collaboration with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA), the Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 to characterize ecosystem responses to land-use changes. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000 and 1973-2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize land-cover change and evaluate using a modified Anderson Land Use Land Cover Classification System for image interpretation. The rates of land-cover change are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change. Additionally, historical aerial photographs from similar timeframes and other ancillary data such as census statistics and published literature are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion. The results illustrate that there is no single profile of land-cover change but instead point to geographic variability that results from land uses within ecoregions continuously adapting to various factors including environmental, technological, and socioeconomic.

Open-File Report↗

Land-cover change in the Lower Mississippi Valley, 1973-2000

The Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. The project is coordinated by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in conjunction with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA). Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 were processed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into four temporal periods: 1973 to1980, 1980 to 1986, 1986 to 1992, 1992 to 2000 and overall from 1973 to 2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize and evaluate land-cover change using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation. The rates of land-cover change were estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images were used to interpret land-cover change. The sample block data then were incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion.

Open-File Report↗

Land-cover change in the Ozark Highlands, 1973-2000

Led by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in collaboration with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA), the Land-Cover Trends Project was initiated in 1999 and aims to document the types, geographic distributions, and rates of land-cover change on a region by region basis for the conterminous United States, and to determine some of the key drivers and consequences of the change (Loveland and others, 2002). For 1973, 1980, 1986, 1992, and 2000 land-cover maps derived from the Landsat series are classified by visual interpretation, inspection of historical aerial photography and ground survey, into 11 land-cover classes. The classes are defined to capture land cover that is discernable in Landsat data. A stratified probability-based sampling methodology undertaken within the 84 Omernik Level III Ecoregions (Omernik, 1987) was used to locate the blocks, with 9 to 48 blocks per ecoregion. The sampling was designed to enable a statistically robust 'scaling up' of the sample-classification data to estimate areal land-cover change within each ecoregion (Loveland and others, 2002; Stehman and others, 2005). At the time of writing, approximately 90 percent of the 84 conterminous United States ecoregions have been processed by the Land-Cover Trends Project. Results from these completed ecoregions illustrate that across the conterminous United States there is no single profile of land-cover/land-use change, rather, there are varying pulses affected by clusters of change agents (Loveland and others, 2002). Land-Cover Trends Project results for the conterminous United States to-date are being used for collaborative environmental change research with partners such as; the National Science Foundation, the National Oceanic and Atmospheric Administration, and the U.S. Fish and Wildlife Service. The strategy has also been adapted for use in a NASA global deforestation initiative, and elements of the project design are being used in the North American Carbon Program's assessment of forest disturbance.

Open-File Report↗

A SAS® code to correct for non-normality and non-constant variance in regression and anova models using the box-cox method of power transormation

A computer program written in SAS ® code for the Box–Cox family of power transformations is presented. The purpose of the program is to suggest a power transformation for the positive continuous response variables in only regression and ANOVA models. A brief overview of data transformation in regression and analysis of variance is given.An example using real data from the U.S. Environmental Protection Agency‘s Environmental Monitoring and Assessment Program/Estuaries (EMAP-E) illustrates the use of the program.

Environmental Monitoring and Assessment↗

Sampling and analysis plan for the water-quality monitoring program in Lake Koocanusa and upper Kootenai River, Montana, water years 2022–23

The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, collected water-quality samples and environmental data in Lake Koocanusa (also known as “Koocanusa Reservoir”), the Kootenai River, and the Tobacco River during water years 2022–23. The transboundary Lake Koocanusa is in southeastern British Columbia, Canada, and northwestern Montana, United States. It was formed by constructing Libby Dam on the Kootenai River 26 kilometers upstream from Libby, Montana. One of the lake sites and the Kootenai River site, in the Libby Dam tailwater (the outflow of the lake flow into the Kootenai River), were equipped with automated, high-frequency ServoSipper water samplers. At the lake site, these samplers were mounted to pontoon platforms during the summer, and a submersible ServoSipper sipper was deployed with ice buoys during the winter. Samples were automatically collected from multiple depths. At the Kootenai River site, these samplers were housed in the gage house. In water year 2022, discrete water-quality samples were collected every 4–6 weeks, year round, at all four lake sites in the Kootenai River between April and November. In water year 2023, discrete water-quality samples were collected at three lake sites and the Kootenai and Tobacco River sites every 4–6 weeks. The goal of this project was to collect multidepth, high-frequency vertical and temporal water-quality samples and data to understand the limnological and biological processes that control variations and trends in selenium concentrations and loads throughout Lake Koocanusa and in the Libby Dam tailwater at the southern end of the lake. This sampling and analysis plan documents the organization, sampling and data-collection scheme and design, pre- and post-collection processes, and quality-assurance and quality-control procedures of the Koocanusa/Kootenai water-quality monitoring program during water years 2022–23.

Montana↗

Sampling and analysis plan for the Koocanusa Reservoir and upper Kootenai River, Montana, water-quality monitoring program, 2021

In 2021, the U.S. Geological Survey will collect water-quality samples and environmental data from 3 sites in Koocanusa Reservoir and from 1 site in the Kootenai River. The transboundary Koocanusa Reservoir is in southeastern British Columbia, Canada, and northwestern Montana, United States, and was formed with the construction of Libby Dam on the Kootenai River 26 kilometers upstream from Libby, Montana. Two of the reservoir sites and the Kootenai River site, in the Libby Dam tailwater (the outflow of the reservoir flow into the Kootenai River), are equipped with automated, high-frequency ServoSipper water samplers. At the two reservoir sites, these samplers are mounted to pontoon platforms and automatically collect samples from multiple depths; a ServoSipper sampler was deployed at one site in 2019, and another ServoSipper sampler will be deployed at a second site in 2021. Discrete water-quality samples will be collected monthly at two depths at the river site and at two of the reservoir sites. The goal of this project is to collect multidepth, high-frequency vertical and temporal water-quality samples and data to understand the limnological and biological processes that control variations and trends in selenium concentrations and loads throughout Koocanusa Reservoir and in the Libby Dam tailwater at the southern end of the reservoir. This sampling and analysis plan documents the organization, sampling and data-collection scheme and design, pre- and post-collection processes, and quality-assurance and quality-control procedures.

Montana↗

Structural equation modeling and the analysis of long-term monitoring data

The analysis of long-term monitoring data is increasingly important; not only for the discovery and documentation of changes in environmental systems, but also as an enterprise whose fruits validate the allocation of effort and scarce funds to monitoring. In simple terms, we may distinguish between the detection of change in some ecosystem attribute versus the investigation of causes and consequences associated with that change. The statistical framework known as structural equation modeling (SEM) can contribute to both detection of changes and the search for causes. This chapter summarizes some of the capabilities of SEM and shows a few ways it can be used to model temporal change. Because of its ability to test hypotheses about whether rates of change are zero or nonzero, it can be used for change detection with repeated-measures data. As more of the capabilities of SEM are presented, its capacity for evaluating causal networks is highlighted. Here is where its potential for making a unique contribution to the analysis of long-term monitoring data is revealed. Thus, one?s primary motivation for using SEM with monitoring data will be to investigate hypotheses about what factors may be driving change. In this chapter, it will be necessary to first introduce notation to describe the elements of structural equation models (SE models) so as to permit an unambiguous presentation of their various forms. The first part of the chapter works through the fundamental features of models of increasing complexity, while the second part of the chapter illustrates several of these possibilities using a real example.

Book chapter↗

Validation of eDNA markers for New Zealand mudsnail surveillance and initial eDNA monitoring at Mississippi River Basin sites

The performance of newly developed New Zealand mudsnail ( Potamopyrgus antipodarum ; NZMS) genetic markers for environmental (eDNA) analysis of water were compared across two laboratories. The genetic markers were tested in four quantitative polymerase chain reaction assays targeting two regions of the NZMS mitochondrial genome, specifically the cytochrome c oxidase subunit 1 (coi) and cytochrome b (cytb) genes. In a blind study, analysts tested each sample eight times with each assay. There were 10 expected-negative samples from the Black River in La Crosse, Wisconsin, 10 expected-positive samples from the Black Earth Creek in Black Earth, Wisconsin, and 10 known-positive samples from the Black River spiked with NZMS DNA. Previously extracted samples, kept at the Upper Midwest Environmental Sciences Center, were pooled by sample location and then equal quantities were distributed between the Upper Midwest Environmental Sciences Center and the Molecular Conservation Genetics Laboratory at the University of Wisconsin-Stevens Point for analysis. The assays tested were (1) the assay targeting cytb with a minor groove binder probe described by Goldberg and others (2013), (2) the cytb assay with a modified double-quenched probe, (3) an assay targeting coi with a double-quenched probe, and (4) a duplex reaction combining the modified cytb assay and the coi assay. Samples were considered positive for the presence of NZMS DNA when quantitative polymerase chain reaction amplification and probe signal was higher than the normalized threshold value above baseline fluorescence. For the duplex assay, samples were considered positive only when both probe signals were higher than the normalized threshold value above baseline fluorescence. Positive results were then confirmed by sequencing the products. All four assays detected the DNA of NZMS in all expected-positive and known-positive samples in both labs. The modified cytb assay, the coi assay, and the duplex assay all failed to detect the DNA of NZMS in all expected-negative samples in both labs. The cytb assay, as described by Goldberg and others (2013), failed to detect the DNA of NZMS in all expected-negative samples for the Molecular Conservation Genetics Laboratory, but some reactions resulted in positive detection in late cycles for 9 of the 10 expected-negative samples at the Upper Midwest Environmental Sciences Center. Amplicons for expected-negative samples with positive reactions were sent for sequencing, and none were confirmed as NZMS. Six amplicons failed to give readable sequences, and three gave sequences without similarity to any known sequence in GenBank. Amplicons from each assay for one representative positive sample were sequenced and identified as NZMS with greater than 99 percent identity. The duplex assay was chosen as the most efficient assay and was used at the Upper Midwest Environmental Sciences Center to analyze triplicate samples from 29 streams in Wisconsin, 8 streams in Illinois, and 8 streams in Iowa. In order to verify results, additional triplicate samples were collected from two of the streams in Iowa and two of the streams in Wisconsin for analysis at the Molecular Conservation Genetics Laboratory. All samples at all sites were negative for NZMS DNA.

Illinois, Iowa, Wisconsin↗

Planning long-term vegetation studies at landscape scales

Long-term ecological research is receiving more attention now than ever before. Two recent books, Long-term Studies in Ecology: Approaches and Alternatives , edited by Gene Likens (1989), and Long-term Ecological Research: An International Perspective , edited by Paul Risser (1991), prompt the question, “Why are these books so thin?” Except for data from paleoecological, retrospective studies (see below), there are exceptionally few long-term data sets in terrestrial ecology (Strayer et al. 1986; Tilman 1989; this volume). In a sample of 749 papers published in Ecology , Tilman (1989) found that only 1.7% of the studies lasted at least five field seasons. Only one chapter in each of the review books dealt specifically with expanding both the temporal and the spatial scales of ecological research (Berkowitz et al. 1989; Magnuson et al. 1991). Judging by the growing number of landscape-scale long-term studies, however, such as the Long-Term Ecological Research (LTER) Program (Callahan 1991), the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program (EMAP; Palmer et al. 1991), the U.S. Army’s Land Condition-Trend Analysis (LCTA) Program (Diersing et al. 1992), and various agencies’ global change research programs (CEES 1993), there is a growing interest to expand ecological research both temporally and spatially.

Book chapter↗

Exploring environmental factors that drive diel variations in tree water storage using wavelet analysis

Internal water storage within trees can be a critical reservoir that helps trees overcome both short- and long-duration environmental stresses. We monitored changes in internal tree water storage in a ponderosa pine on daily and seasonal scales using moisture probes, a dendrometer, and time-lapse electrical resistivity imaging (ERI). These data were used to investigate how patterns of in-tree water storage are affected by changes in sapflow rates, soil moisture, and meteorologic factors such as vapor pressure deficit. Measurements of xylem fluid electrical conductivity were constant in the early growing season while inverted sapwood electrical conductivity steadily increased, suggesting that increases in sapwood electrical conductivity did not result from an increase in xylem fluid electrical conductivity. Seasonal increases in stem electrical conductivity corresponded with seasonal increases in trunk diameter, suggesting that increased electrical conductivity may result from new growth. On the daily scale, changes in inverted sapwood electrical conductivity correspond to changes in sapwood moisture. Wavelet analyses indicated that lag times between inverted electrical conductivity and sapflow increased after storm events, suggesting that as soils wetted, reliance on internal water storage decreased, as did the time required to refill daily deficits in internal water storage. We found short time lags between sapflow and inverted electrical conductivity with dry conditions, when ponderosa pine are known to reduce stomatal conductance to avoid xylem cavitation. A decrease in diel amplitudes of inverted sapwood electrical conductivity during dry periods suggest that the ponderosa pine relied on internal water storage to supplement transpiration demands, but as drought conditions progressed, tree water storage contributions to transpiration decreased. Time-lapse ERI- and wavelet-analysis results highlight the important role internal tree water storage plays in supporting transpiration throughout a day and during periods of declining subsurface moisture.

Colorado↗

Evidence for fish dispersal from spatial analysis of stream network topology

Developing spatially explicit conservation strategies for stream fishes requires an understanding of the spatial structure of dispersal within stream networks. We explored spatial patterns of stream fish dispersal by evaluating how the size and proximity of connected streams (i.e., stream network topology) explained variation in fish assemblage structure and how this relationship varied with local stream size. We used data from the US Environmental Protection Agency's Environmental Monitoring and Assessment Program in wadeable streams of the Mid-Atlantic Highlands region (n = 308 sites). We quantified stream network topology with a continuous analysis based on the rate of downstream flow accumulation from sites and with a discrete analysis based on the presence of mainstem river confluences (i.e., basin area >250 km2) within 20 fluvial km (fkm) from sites. Continuous variation in stream network topology was related to local species richness within a distance of ???10 fkm, suggesting an influence of fish dispersal within this spatial grain. This effect was explained largely by catostomid species, cyprinid species, and riverine species, but was not explained by zoogeographic regions, ecoregions, sampling period, or spatial autocorrelation. Sites near mainstem river confluences supported greater species richness and abundance of catostomid, cyprinid, and ictalurid fishes than did sites >20 fkm from such confluences. Assemblages at sites on the smallest streams were not related to stream network topology, consistent with the hypothesis that local stream size regulates the influence of regional dispersal. These results demonstrate that the size and proximity of connected streams influence the spatial distribution of fish and suggest that these influences can be incorporated into the designs of stream bioassessments and reserves to enhance management efficacy. ?? 2008 by The North American Benthological Society.

Journal of the North American Benthological Societ↗

Use of semipermeable membrane devices for in situ monitoring of polycyclic aromatic hydrocarbons in aquatic environments

A method is given for the recovery, cleanup, and analysis of polycyclic aromatic hydrocarbons (PAHs) that have been sequestered in SPMDs (semipermeable membrane devices). SPMDs are polymeric membranes enclosing lipids, and mimic the bioconcentration process of aquatic animals. SPMDs are used as passive, in situ monitors of contamination by organic pollutants of aquatic environments. The method reported here includes dialytic recovery of the PAHs, cleanup of the dialysates using size exclusion, adsorption, and argentation chromatographic modules in tandem, then analysis by gas chromatography with photoionization or mass spectrometric detection. The method is demonstrated to overcome the presence of a variety of environmental co-contaminants and other potential interferents in the dialysates. A field application is also demonstrated in which SPMDs are used to monitor PAH contamination in an urban creek. Approaches to the use of SPMD data to calculate aqueous concentrations of PAHs are discussed. The use of SPMDs in combination with the complementary, PAH-specific cleanup procedure provides a unique approach to the analysis of PAH residues in the aquatic environment.

Chemosphere↗

Contemporary environmental assessment using a viability analysis in a large river system to inform restoration and adaptive management decisions

As large-scale restoration plans for degraded aquatic habitats evolve, it is essential that multiorganizational collaborations have a common vision to achieve consensus on restoration goals. Development of restoration targets and postrestoration monitoring strategies can be focused using a viability analysis framework that supports an adaptive management process. Viability analysis is a robust and accommodating framework, adaptable to any restoration monitoring program and, through the determination of common desired endpoints, can aid consensus building and collaboration across jurisdictional boundaries. In the St. Clair-Detroit River System, which is the Great Lakes connecting channel between southern Lake Huron and western Lake Erie, a viability analysis framework was used to evaluate environmental parameters associated with fisheries and aquatic restoration efforts and to gauge the overall health of the aquatic environment. Steps to derive the viability analysis were as follows: (1) establishing meaningful baseline metrics, (2) identifying information deficiencies, and (3) placing the context of current conditions into a usable format for managers and practitioners. Most geographic segments were designated in overall fair condition, and the conservation targets were designated in either good or fair condition, based on available assessed indicators. Many indicators were unable to be assessed or assigned condition status, which identified research and monitoring data gaps. Metrics associated with native migratory fishes, Lake St. Clair, and islands are generally in better condition than metrics associated with the coastal terrestrial systems, aerial migrants, and coastal wetlands. These results were not unexpected given the highly urbanized landscape of the St. Clair-Detroit River System. Resource managers in the corridor can use these results to identify knowledge gaps, research and restoration priorities, and to assess progress towards meeting restoration goals.

Michigan, Ontario↗